1. Field of the Invention
The present invention relates to systems and methods used for manipulating physical objects. In particular, the present invention relates to a method for the selection of physical objects in a robot system.
2. Description of the Related Art
Robot systems have widely been used in many industries to perform repetitive tasks that require little capability to actually model visually or cognitively physical objects being manipulated or that require little skill to take a hold on and to move. Robots can also be built to work in environments hostile to human floor workers or to be able to work with material hazardous to humans such as toxic or radioactive materials, waste or massive objects. It is desirable to make such robot systems as autonomous as possible to minimize the amount of human involvement needed.
When the aim is to have the robot arm to manipulate objects, the robot arm is commonly equipped with a device suitable for gripping the objects of interest. Such a device can, for example, resemble a hand, a claw or a clamp. While programming the robot to perform repetitive tasks is relatively easy, there are difficult problems in automatically manipulating objects, especially related to recognizing the objects from a varying environment or an environment crowded with other objects, and manipulating an object which resides among other objects. Namely, other objects may cover the object partially or in whole, thus making it difficult to pin down the exact location of the object to instruct the robot arm to move to, or the other objects can obstruct the movements of a robot hand thereby making pre-programmed movements unsuitable for the task.
The problem of recognizing objects is commonly dealt with using pattern recognition algorithms, which search for objects in sensory data such as digital camera images. Such algorithms are an actively studied field. While there are many algorithms which can even recognize objects against an uneven background, pattern recognition algorithms generally work best when the background is both uniform and predetermined. Previously, objects of predetermined type have been searched from a clear operating area and they been selected from the operating area as recognized objects. Sets of actions can be performed on a selected object of a known type. The set of actions can be chosen based on the type of the object, for example placing different kinds of objects in different bins.
However, there are possibilities for error in determining of the type of an object. For example, image recognition algorithms can produce false results, identifying an object as that of a wrong type. Further, even if the object has been correctly recognized, the gripper could fail to grip the intended object, for example, if the intended object is obscured by another object which could get gripped instead, or if the gripper is not moved to the right position before gripping as a result of inaccuracies in controlling the robot arm. There is also the possibility that several objects are inadvertently gripped at the same time, for example, if the objects are located close together or they are stuck together. In applications such as recycling and waste management, it is important that the purity of a sorted group of objects is high, namely, that as few as possible objects of a wrong type end up in the sorted groups of objects.